Abstract
We have developed a small scale four-layered neural network (NN) model for simple character recognition, which can recognize the patterns transformed by affine conversion. It learns by backpropagation to obtain the characteristics of the simple cell and the complex cell in the visual cortex. In this study 24 patterns are presented as input patterns. An input pattern is divided into 64 local patterns and connected with the 1st hidden layer as in the visual cortex. The proposed NN model has good performance of the feature extraction in first layers.
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© 2003 Springer-Verlag Berlin Heidelberg
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Shintani, H., Nagashino, H., Akutagawa, M., Kinouchi, Y. (2003). A Neural Network Model for Pattern Recognition. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2774. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45226-3_111
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DOI: https://doi.org/10.1007/978-3-540-45226-3_111
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40804-8
Online ISBN: 978-3-540-45226-3
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